kodwai

For me it's whether the agent asks clarifying questions in the first 30 seconds. If it just starts coding, I know I'll be cleaning up assumptions for the next hour. If it asks "do you want me to handle X case?" before writing anything, the session almost always goes well. Bad sessions are confidently wrong. Good sessions are loudly uncertain.

Love this, we've gone from "How good are you at coding?" to "How good are you at collaborating with AI?" and honestly... that's a much more relevant question today.The idea of scoring Direction instead of just the final output is what caught my attention. Looking forward to throwing Claude Code at a few challenges this weekend and seeing whether I'm actually a good AI engineer or just really good at accepting suggestions.Congrats on the launch! 🚀

Hey Product Hunt, I'm Hakan, founder of Kodwai.Three years ago we typed every line. Now most of us code by directing an agent, steering it, checking it, catching it when it's confidently wrong. That's the real skill, and nothing measures it. LeetCode tests memorized algorithms. Take-homes test free time. Neither reflects how we actually work.So I built Kodwai. Pick a real challenge, solve it on your own machine with your own agent (Claude Code, Cursor, or Codex), and submit. We score the session across three axes: Direction (how you steer and verify), Outcome (what shipped and whether it passes), and Lift (the edge cases a one-shot prompt misses). Every score points to the evidence behind it.Direction is half the weight on purpose. A careless prompt that passes the tests still scores low, because steering the agent well was always the hard part.Free for developers, with a public leaderboard and a profile you can send instead of doing a take-home. Teams can run interviews on the same engine and watch the real session.When you pair with an agent, what tells you it's going well or badly? That's what I'm trying to measure, and I'll be here all day. kodwai.com